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Cause or effect? Looking beyond correlation
Thu, 6 Apr 2017, 18:00
A public lecture by
Peter Bühlmann, ETH Zürich
Is it a cause or an effect? This simple but fundamental question is often asked in society and science. Searching for the causes for a certain disease and quantifying their effects on the disease status is a long-standing problem in medical studies. Considering correlations among measured variables is insufficient for distinguishing cause from effect. The classical and well-developed framework for causal inference is based on randomised studies; with the drawback that they are often very expensive or even impossible to do due to ethical reasons. Recent approaches try to ``substitute in part'' the randomised studies by models, algorithms and statistical techniques. Although thought-provoking, they can be particularly attractive in nowadays Big Data settings.
Doors open at 17:30. The talk will be followed by an informal reception to which all ticket holders are invited.